Embodiments of the present specification generally relate to photon-counting computed tomography imaging systems, and more specifically to a system and method for enhancing image quality in photon-counting computed tomography systems via use of a model that incorporates unique statistical properties of X-ray pile-up.
Radiographic imaging systems, such as X-ray and computed tomography (CT) systems have been employed for observing interior aspects of objects. Typically, the imaging systems include an X-ray source that is configured to emit X-rays toward an object of interest, such as a patient, a work piece, a parcel, a piece of luggage, and so forth. A detecting device, such as an array of radiation detectors, is positioned on the opposite side of the object and is configured to detect the X-rays transmitted through the object.
As will be appreciated, a CT scan is conducted by measuring a series of projection measurements from many different angles around a patient or object. These measurements are combined into a sinogram, which collects the projection data from multiple views into a single data set. A reconstruction algorithm is used to process the sinogram to produce an image representing the patient or object. Currently, there exist multiple methods for image reconstruction. In recent years, statistical iterative reconstruction (SIR) methods have been used to produce images of very high quality, while reducing the required radiation dose.
Using the SIR method, the objective is to produce reconstructed images that would result in estimated sinograms that best match a set of measured sinograms collected from a CT scan. On each iteration of the SIR method, the reconstructed image and the known geometry and other characteristics of the CT system are used by a forward model to compute the estimated sinogram that would be produced by the reconstructed image. The forward model essentially simulates the attenuation of X-rays as they pass from the X-ray source, through the patient, as represented by the reconstructed images, and into the detector of the CT system.
Subsequently, the estimated sinogram is compared with the measured sinogram from the CT scan. Based on this comparison, an updated reconstructed image is computed that is configured to make the sinogram estimated by the forward model more similar to the measured sinogram in the subsequent iteration. Typically, the update step is performed as an optimization of an objective function.
Conventional CT and other radiographic imaging systems utilize detectors that convert radiographic energy integrated over a time period into electrical current signals, which are ultimately digitized. A drawback of such detectors however is their inability to provide data or feedback regarding the number and/or energy of detected photons. Energy-discriminating, direct-conversion detectors that are capable of counting X-rays detected during a period of time and providing a measurement of the energy level of each X-ray detected have been employed in prototype CT systems. However, a drawback of these direct-conversion semiconductor detectors is their inability to count at the X-ray photon flux rates typically encountered with conventional CT systems.
Photon-counting CT systems record individual X-ray photons as the photons reach the detector. Disadvantageously, the photon-counting CT systems are unable to efficiently count X-rays that arrive too close together in time. This is typically a problem for measurements at high X-ray flux, and/or in regions of a sinogram including little attenuation through the patient and/or the X-ray source pre-patient filter (bowtie). Certain techniques for a photon-counting CT system to account for pile-up entail correcting the measured sinograms before comparing the estimated sinogram with the measured sinogram.
However, in addition to impacting the number of counts recorded, pile-up also impacts the noise in CT projection data. Noise in projection measurements typically increase with the X-ray flux, following approximately a Poisson distribution. Disadvantageously, when pile-up occurs, both the number of counts and the variation in counts are reduced.
Further, the very high X-ray photon flux rate has been known to cause pile-up and polarization in certain direct-conversion devices that ultimately leads to detector saturation. “Pile-up” is a phenomenon that occurs when X-ray flux incident at the detector is so high that there is a non-negligible possibility that two or more X-ray photons interact with the direct-conversion sensor and deposit charge packets in a single pixel (“photon pile-up”), or in neighboring pixels (“pattern pile-up”), during one charge-integration cycle. In such cases, these events are recognized as one single event having the sum of the individual photon energies. If this happens sufficiently often, a significant distortion of the detected spectrum may result as piled-up events are shifted in the spectrum to higher energies. In addition, pile-up leads to a more or less pronounced depression of efficiency in a projection area including lower attenuation, resulting in flux detection loss. In particular, these detectors typically saturate at relatively low X-ray flux levels. Above these levels, the detector response is less predictable and has degraded dose utilization. That is, once a pixel is saturated (corresponding to higher values in the measured photon counts), additional radiation will not produce useful information in the measurements.
As known in the art, energy-discriminating photon detection systems place X-rays into one or more energy bins. One type of processing of energy bin values called Optimal Energy Weighting (OEW) may enhance the contrast-to-noise ratio relative to a conventional CT system which employs an energy-integration process (the total energy deposited during an acquisition interval is summed). Another type of processing of multiple energy-bin data is called Material Decomposition and is configured to extract quantitative tissue compositional information, if sufficient photon statistics exist, by processing data from multiple energy bins. In particular, photon-counting detectors make it possible to improve image quality and may offer new kinds of tissue compositional information than conventional energy-integrating systems.
Further, as will be appreciated, detector saturation leads to corruption of imaging information and consequently results in noise and artifacts in X-ray projection data and reconstructed CT images. Photon-counting direct-conversion detectors are known to suffer from decreased detector quantum efficiency (DQE) at high count rates mainly due to detector pile-up. In particular, photon-counting direct-conversion detectors incur pile-up due to the intrinsic charge collection time (i.e., dead time) associated with each X-ray photon event. As indicated above, saturation ultimately is often due to pulse pile-up, particularly when the X-ray photon absorption rate for each pixel is on the order of the inverse of this charge collection time. The reciprocal of the charge collection time is called the maximum periodic rate (MPR). When the true mean X-ray count rate incident on the detector is equal to the maximum periodic rate, the recorded counts are one half the input detected counts and the output count rate is only one half the MPR. Reduced DQE results in reduced image quality, i.e., a noisier image. In addition, hysteresis and other non-linear effects occur at flux levels near and above detector saturation and lead to additional image artifacts.
In addition, the relationship between the true signal and the measured signal becomes non-linear, showing a reduction as the count rate is increased. This pile-up effect, if stable, may be calibrated and corrected, thereby increasing the effective count rate capability of the detector, albeit with a penalty of higher noise. However, if the count rate is increased to a point where the relationship between the true signal and the measured signal becomes non-monotonic, which is a characteristic of paralyzable electronics, correction of this non-monotonic relationship may no longer be practical. In particular, when the detector is over-ranged, the recorded count rate may be non-monotonic for increasing flux rate for paralyzable electronics or becomes the maximum achievable count rate for non-paralyzable electronics.
Previously conceived solutions to enable photon counting at high X-ray flux rates include using bowtie shaped filters to pre-condition the flux rate at the detector, compensating for the patient shape. Also, it has been proposed to subdivide the pixel into multiple sub-pixels, each sub-pixel connected to its own preamplifier and associated electronics. By reducing the area of the direct conversion sub-pixel, the flux rate capability may be increased as fewer photons are collected in the smaller area during an acquisition interval. However, the signal-to-noise ratio of the resulting signal may be reduced, and the level of crosstalk, both in terms of photons and deposited charge between neighboring detector pixels may be disadvantageously significant due to the increased perimeter between sub-pixels.